In line with a recent revolutionary trend in the retailing industry, retail firms often adopt omni-channel strategies. In an omni-channel retail environment, a firm aims to provide a seamless experience for customers to access multiple channels in purchasing goods. For example, a customer may visit a retail store to physically browse items, and via an on-line sales infrastructure, then order online from the same retailer. Alternatively, a customer may order online but then pick up the purchased item at a retail store. In today's increasingly mobile world, where prices across a retailer's sales channels are available to customers, customers increasingly engage in channel-switching behavior due to differences in price cadences across channels.
Many retailers are making concerted strategic decisions to break down traditional boundaries between channels in the design of their retail supply chains. For example, retailers recognize their network of physical “brick-and-mortar” stores can also serve the purpose of a network of mini-warehouses to fulfill e-commerce sales. This is accomplished through multiple cross-channel fulfillment alternatives, including the retailer-initiated ship from store (SFS) option (i.e., the retailer opts to fulfill an e-commerce sale from one of its stores, which picks, packs, and ships the product to the customer's address) and the customer-initiated buy-online-pickup-in-store (BOPS) option (i.e., the customer chooses to pick up the product from a nearby store).
A hallmark of an omni-channel retail environment is that inventory is shared across channels, both from the customer's perspective and from the retailer's perspective. In the customer's perspective, he or she can choose a channel to purchase from based on the price and convenience. In the retailer's perspective, it has the ability to choose a channel to fulfill a transaction.
Illustrative of a lifecycle demand profile for an electronic product sold by a retailer who uses SFS to fulfill online orders, FIG. 1A shows a plot 50 of actual store arrivals (market size demand) 53 vs. a prior predicted sales demand (market size) 55 for an example product over a time span of weeks 20-52 where the last 12 weeks represent a “clearance” period. As shown, towards the end of life of for short lifecycle items, sales are constrained by available inventory. Out-of-stock induces results in lost-sales opportunities as well as channel switching. This complicates predicted channel specific unconstrained demand, significantly impacting forecast accuracy which in turn results in poor downstream decisions such as markdown pricing. As shown in FIG. 1A, inventory “effects” is not the same as total unavailability (stock-outs). As shown in FIG. 1A, there is more than a predicted decline in the brick-and-mortar sales channel. FIG. 1B shows an example plot 60 of actual in-store sales 63 vs. a prior predicted sales 65 and illustrates at 66 the latent acceleration in brick sales decay of product sold by an example retailer, e.g., over a 12 week clearance period, due to SFS decisions. Moreover, during the clearance period, e.g., last 12 weeks shown in chart, customers increasingly switch to on-line channel as shown in the plot 70 of FIG. 1C depicting actual on-line sales 73 vs. predicted on-line sales 75. This SFS “inventory effect” is most prominent during the end of a selling season and by ignoring SFS cross-channel fulfillment impact, there may be systematic predicted overestimates of brick sales and underestimates online sales.
This complicates efforts to predict demands for the product, leading to mis-pricing and potential loss of revenue.